Sistema de control multipropósito programable por pulsación de teclas con álgebra RPN.

[ES]Para la elaboración del presente proyecto, primeramente se explicara los requerimientos técnicos y el origen del microprocesador a utilizar para poder situar y centrar el tema del trabajo. Una vez acotado y delimitado el tema objeto de estudio, se planteara una arquitectura de software sobre la posibilidad de generar unas “pseudolibrerias” de mayor nivel de programación que el ensamblador. Posteriormente, se verificara la posible viabilidad o no de tal planteamiento, exponiendo sus resultados y las consideraciones oportunas a las que nos ha llevado su estudio. Para ello se analizara en una primera instancia el microprocesador a utilizar, que será el PIC16F887, centrándonos en el debido al amplio manejo y conocimiento que poseemos sobre este microprocesador. El objeto de este escrito será presentar una oferta económica relativa al desarrollo e instalación de dichos microprocesadores para la mejora en el ámbito industrial. Finalmente, realizaremos un estudio sobre la implementación de este tipo de arquitectura software en diferentes microprocesadores de mayores prestaciones, estudiando si la infraestructura será eficiente, funcional y económica.

Biotic vs. Abiotic Control of Decomposition: A Comparison of the Effects of Simulated Extinctions and Changes in Temperature

The loss of species is known to have significant effects on ecosystem functioning, but only recently has it been recognized that species loss might rival the effects of other forms of environmental change on ecosystem processes. There is a need for experimental studies that explicitly manipulate species richness and environmental factors concurrently to determine their relative impacts on key ecosystem processes such as plant litter decomposition. It is crucial to understand what factors affect the rate of plant litter decomposition and the relative magnitude of such effects because the rate at which plant litter is lost and transformed to other forms of organic and inorganic carbon determines the capacity for carbon storage in ecosystems and the rate at which greenhouse gasses such as carbon dioxide are outgassed. Here we compared how an increase in water temperature of 5 degrees C and loss of detritivorous invertebrate and plant litter species affect decomposition rates in a laboratory experiment simulating stream conditions. Like some prior studies, we found that species identity, rather than species richness per se, is a key driver of decomposition, but additionally we showed that the loss of particular species can equal or exceed temperature change in its impact on decomposition. Our results indicate that the loss of particular species can be as important a driver of decomposition as substantial temperature change, but also that predicting the relative consequences of species loss and other forms of environmental change on decomposition requires knowledge of assemblages and their constituent species' ecology and ecophysiology

Robust Sliding Control of SEIR Epidemic Models

This paper is aimed at designing a robust vaccination strategy capable of eradicating an infectious disease from a population regardless of the potential uncertainty in the parameters defining the disease. For this purpose, a control theoretic approach based on a sliding-mode control law is used. Initially, the controller is designed assuming certain knowledge of an upper-bound of the uncertainty signal. Afterwards, this condition is removed while an adaptive sliding control system is designed. The closed-loop properties are proved mathematically in the nonadaptive and adaptive cases. Furthermore, the usual sign function appearing in the sliding-mode control is substituted by the saturation function in order to prevent chattering. In addition, the properties achieved by the closed-loop system under this variation are also stated and proved analytically. The closed-loop system is able to attain the control objective regardless of the parametric uncertainties of the model and the lack of a priori knowledge on the system.

Evaluation of wave drag reduction by flow control

An analytical expression is proposed to estimate the wave drag of an aerofoil equipped with shock control. The analysis extends the conventional approach for a single normal shock wave, based on the knowledge that all types of successful shock control on transonic aerofoils cause bifurcated λ-shock structures. The influence of surface curvature on the λ-shock structure has been taken into account. The extended method has been found to produce fairly good agreement with the results obtained by CFD methods while requiring negligible computational effort. This new formulation is expected to be beneficial in the industrial design process of transonic aerofoils and wings where a large number of computational simulations have to be performed.

Adaptive control of combustion instabilities for unknown sign of the high frequency gain

A type of adaptive, closed-loop controllers known as self-tuning regulators present a robust method of eliminating thermoacoustic oscillations in modern gas turbines. These controllers are able to adapt to changes in operating conditions, and require very little pre-characterisation of the system. One piece of information that is required, however, is the sign of the system's high frequency gain (or its 'instantaneous gain'). This poses a problem: combustion systems are infinite-dimensional, and so this information is never known a priori. A possible solution is to use a Nussbaum gain, which guarantees closed-loop stability without knowledge of the sign of the high frequency gain. Despite the theory for such a controller having been developed in the 1980s, it has never, to the authors' knowledge, been demonstrated experimentally. In this paper, a Nussbaum gain is used to stabilise thermoacoustic instability in a Rijke tube. The sign of the high frequency gain of the system is not required, and the controller is robust to large changes in operating conditions - demonstrated by varying the length of the Rijke tube with time. Copyright © 2008 by Simon J. Illingworth & Aimee S. Morgans.

The Acquisition of an Inheritable 50-bp Deletion in the Human mtDNA Control Region Does Not Affect the mtDNA Copy Number in Peripheral Blood Cells

The mitochondrial DNA (mtDNA) control region is believed to play an important biological role in mtDNA replication. Large deletions in this region are rarely found, but when they do occur they might be expected to interfere with the replication of the molecule, thus leading to a reduction of mtDNA copy number. During a survey for mtDNA sequence variations in 5,559 individuals from the general Chinese population and 2,538 individuals with medical disorders, we identified a 50-bp deletion (m.298_347del50) in the mtDNA control region in a member of a healthy Han Chinese family belonging to haplogroup B4c1b2, as suggested by complete mtDNA genome sequencing. This deletion removes the conserved sequence block II (CSBII; region 299-315) and the replication primer location (region 317-321). However, quantification of the mtDNA copy number in this subject showed a value within a range that was observed in 20 healthy subjects without the deletion. The deletion was detected in the hair samples of the maternal relatives of the subject and exhibited variable heteroplasmy. Our current observation, together with a recent report for a benign 154-bp deletion in the mtDNA control region, suggests that the control of mtDNA replication may be more complex than we had thought. Hum Mutat 31:538-543, 2010. (C) 2010 Wiley-Liss, Inc.

Motor control is decision-making.

Motor behavior may be viewed as a problem of maximizing the utility of movement outcome in the face of sensory, motor and task uncertainty. Viewed in this way, and allowing for the availability of prior knowledge in the form of a probability distribution over possible states of the world, the choice of a movement plan and strategy for motor control becomes an application of statistical decision theory. This point of view has proven successful in recent years in accounting for movement under risk, inferring the loss function used in motor tasks, and explaining motor behavior in a wide variety of circumstances.

Reinforcement learning with reference tracking control in continuous state spaces

The contribution described in this paper is an algorithm for learning nonlinear, reference tracking, control policies given no prior knowledge of the dynamical system and limited interaction with the system through the learning process. Concepts from the field of reinforcement learning, Bayesian statistics and classical control have been brought together in the formulation of this algorithm which can be viewed as a form of indirect self tuning regulator. On the task of reference tracking using a simulated inverted pendulum it was shown to yield generally improved performance on the best controller derived from the standard linear quadratic method using only 30 s of total interaction with the system. Finally, the algorithm was shown to work on the simulated double pendulum proving its ability to solve nontrivial control tasks. © 2011 IEEE.

Motor control is decision-making

© 2012 Elsevier Ltd. Motor behavior may be viewed as a problem of maximizing the utility of movement outcome in the face of sensory, motor and task uncertainty. Viewed in this way, and allowing for the availability of prior knowledge in the form of a probability distribution over possible states of the world, the choice of a movement plan and strategy for motor control becomes an application of statistical decision theory. This point of view has proven successful in recent years in accounting for movement under risk, inferring the loss function used in motor tasks, and explaining motor behavior in a wide variety of circumstances.

Formal specification and refinement of a safe train control function

Motivated by the design and development challenges of the BART case study, an approach for developing and analyzing a formal model for reactive systems is presented. The approach makes use of a domain specific language for specifying control algorithms able to satisfy competing properties such as safety and optimality. The domain language, called SPC, offers several key abstractions such as the state, the profile, and the constraint to facilitate problem specification. Using a high-level program transformation system such as HATS being developed at the University of Nebraska at Omaha, specifications in this modelling language can be transformed to ML code. The resulting executable specification can be further refined by applying generic transformations to the abstractions provided by the domain language. Problem dependent transformations utilizing the domain specific knowledge and properties may also be applied. The result is a significantly more efficient implementation which can be used for simulation and gaining deeper insight into design decisions and various control policies. The correctness of transformations can be established using a rewrite-rule based induction theorem prover Rewrite Rule Laboratory developed at the University of New Mexico.

Toward high-performance polymer solar cells: The importance of morphology control

Polymer solar cells have the potential to become a major electrical power generating tool in the 21st century. R&D endeavors are focusing on continuous roll-to-roll printing of polymeric or organic compounds from solution-like newspapers-to produce flexible and lightweight devices at low cost. It is recognized, though, that besides the functional properties of the compounds the organization of structures on the nanometer level-forced and controlled mainly by the processing conditions applied-determines the performance of state-of-the-art polymer solar cells. In such devices the photoactive layer is composed of at least two functional materials that form nanoscale interpenetrating phases with specific functionalities, a so-called bulk heterojunction. In this perspective article, our current knowledge on the main factors determining the morphology formation and evolution is introduced, and gaps of our understanding on nanoscale structure-property relations in the field of high-performance polymer solar cells are addressed. Finally, promising routes toward formation of tailored morphologies are presented.

Meta-Rules: Reasoning About Control

How can we insure that knowledge embedded in a program is applied effectively? Traditionally the answer to this question has been sought in different problem solving paradigms and in different approaches to encoding and indexing knowledge. Each of these is useful with a certain variety of problem, but they all share a common problem: they become ineffective in the face of a sufficiently large knowledge base. How then can we make it possible for a system to continue to function in the face of a very large number of plausibly useful chunks of knowledge? In response to this question we propose a framework for viewing issues of knowledge indexing and retrieval, a framework that includes what appears to be a useful perspective on the concept of a strategy. We view strategies as a means of controlling invocation in situations where traditional selection mechanisms become ineffective. We examine ways to effect such control, and describe meta-rules, a means of specifying strategies which offers a number of advantages. We consider at some length how and when it is useful to reason about control, and explore the advantages meta-rules offer for doing this.

Control of Vibration in Mechanical Systems Using Shaped Reference Inputs

Dynamic systems which undergo rapid motion can excite natural frequencies that lead to residual vibration at the end of motion. This work presents a method to shape force profiles that reduce excitation energy at the natural frequencies in order to reduce residual vibration for fast moves. Such profiles are developed using a ramped sinusoid function and its harmonics, choosing coefficients to reduce spectral energy at the natural frequencies of the system. To improve robustness with respect to parameter uncertainty, spectral energy is reduced for a range of frequencies surrounding the nominal natural frequency. An additional set of versine profiles are also constructed to permit motion at constant speed for velocity-limited systems. These shaped force profiles are incorporated into a simple closed-loop system with position and velocity feedback. The force input is doubly integrated to generate a shaped position reference for the controller to follow. This control scheme is evaluated on the MIT Cartesian Robot. The shaped inputs generate motions with minimum residual vibration when actuator saturation is avoided. Feedback control compensates for the effect of friction Using only a knowledge of the natural frequencies of the system to shape the force inputs, vibration can also be attenuated in modes which vibrate in directions other than the motion direction. When moving several axes, the use of shaped inputs allows minimum residual vibration even when the natural frequencies are dynamically changing by a limited amount.

Roles of Knowledge in Motor Learning

The goal of this thesis is to apply the computational approach to motor learning, i.e., describe the constraints that enable performance improvement with experience and also the constraints that must be satisfied by a motor learning system, describe what is being computed in order to achieve learning, and why it is being computed. The particular tasks used to assess motor learning are loaded and unloaded free arm movement, and the thesis includes work on rigid body load estimation, arm model estimation, optimal filtering for model parameter estimation, and trajectory learning from practice. Learning algorithms have been developed and implemented in the context of robot arm control. The thesis demonstrates some of the roles of knowledge in learning. Powerful generalizations can be made on the basis of knowledge of system structure, as is demonstrated in the load and arm model estimation algorithms. Improving the performance of parameter estimation algorithms used in learning involves knowledge of the measurement noise characteristics, as is shown in the derivation of optimal filters. Using trajectory errors to correct commands requires knowledge of how command errors are transformed into performance errors, i.e., an accurate model of the dynamics of the controlled system, as is demonstrated in the trajectory learning work. The performance demonstrated by the algorithms developed in this thesis should be compared with algorithms that use less knowledge, such as table based schemes to learn arm dynamics, previous single trajectory learning algorithms, and much of traditional adaptive control.

Coherent Behavior from Incoherent Knowledge Sources in the Automatic Synthesis of Numerical Computer Programs

A fundamental problem in artificial intelligence is obtaining coherent behavior in rule-based problem solving systems. A good quantitative measure of coherence is time behavior; a system that never, in retrospect, applied a rule needlessly is certainly coherent; a system suffering from combinatorial blowup is certainly behaving incoherently. This report describes a rule-based problem solving system for automatically writing and improving numerical computer programs from specifications. The specifications are in terms of "constraints" among inputs and outputs. The system has solved program synthesis problems involving systems of equations, determining that methods of successive approximation converge, transforming recursion to iteration, and manipulating power series (using differing organizations, control structures, and argument-passing techniques).